System to quantify consumer preferences

ABSTRACT

A system to determine preference information of part worth values associated with a consumer and a product includes determination of a plurality of attributes of the product, each of the plurality of attributes associated with a plurality of attribute levels, determination of a plurality of piles of attributes based on a first indication of the consumer, each of the plurality of piles comprising one or more of the plurality of attributes, determination of a ranked order of a plurality of attributes of one of the plurality of piles, determination of a relative importance of one or more of the plurality of attributes of the one of the plurality of piles based on a second indication of the consumer, determination of a scale value of one or more attribute levels of the one or more of the plurality of attributes of the one of the plurality of piles based on a third indication of the consumer, and determination of a part worth value associated with an attribute level of one of the plurality of attributes of the one of the plurality of piles based on a determined scale value of the attribute level and a determined relative importance of the one of the plurality of attributes.

BACKGROUND OF THE INVENTION

[0001] 1. Field of the Invention

[0002] The present invention relates to systems for determining consumerpreferences. More specifically, the invention relates to self-explicatedtrade-off analysis systems used to quantify consumer preferences withrespect to product attributes and to product attribute levels.

[0003] 2. Description of the Related Art

[0004] Manufacturers are presented with many choices during the designof a product. For example, a manufacturer must choose from among severalavailable product features, or attributes, when deciding whichattributes to include in a product. Some attributes are optional whileothers must be included. In the case of a television set, “Chassiscolor” is an attribute that must be included and “Picture-in-picture” isan optional attribute. For each included attribute, a manufacturer mustalso choose an attribute level to associate with the attribute.Attribute levels which may be associated with the attribute “Chassiscolor” include “black”, “white”, “blue”, etc.

[0005] Occasionally, a manufacturer produces several versions of asimilar product by varying product attributes and/or attribute levelsamong the several versions. In such a case, the manufacturer mustdetermine attributes and associated attribute levels to include in eachversion as described above. Moreover, the manufacturer must determinehow many units of each version will be produced. For example, amanufacturer choosing to produce televisions having a black chassis andtelevisions having a blue chassis must also determine how many of eachtype of television to produce and offer for sale.

[0006] Product pricing represents a further choice presented to productmanufacturers. In this regard, a manufacturer attempts to choose a pricefor each produced product that will maximize overall profit to themanufacturer. Of course, price may also be considered a productattribute, with associated attribute levels consisting of particularprices.

[0007] Each of the foregoing choices may be greatly facilitated if themanufacturer has detailed and accurate information relating to consumerpreferences. A consumer, in this regard, is any entity to which aproduct and/or service may be offered. Such consumers includeindividuals, businesses, and purchasing managers. Consumer preferenceinformation can be used to determine the popularity and desirability toconsumers of particular product attributes and attribute levels.Therefore, by using this information, a manufacturer is more likely tochoose product configurations as well as production amounts and pricesfor each product configuration that maximize overall profit.

[0008] In view of its importance, manufacturers expend significantresources in their attempts to obtain detailed and accurate consumerpreference information and to analyze marketplace choices. Theseresources are most commonly allotted to conventional consumer surveys.Such surveys typically consist of a list of predetermined questionsdesigned to elicit information from a consumer regarding the consumer'sfeelings toward products, product attributes, and product attributelevels. Surveys may be administered randomly, for example by stoppingconsumers at shopping malls or other retail areas, or by contactingspecific consumers who are targeted because they are members of ademographic group about which information is desired.

[0009] Conventional surveys present several inherent drawbacks. First,since survey results are compiled into general demographic categories,surveys merely determine, at best, preferences of a theoretical averageconsumer belonging to each demographic category. Accordingly, surveyresults are only marginally correlated to any one consumer'spreferences. Therefore, such results lack predictive precision of aparticular consumer's preferences with respect to marketplace choicesavailable and not yet available. Second, although conventional surveysmay indicate whether one attribute level (e.g. “black chassis color”) isgenerally preferred over another level of the same attribute (whitechassis color”), such surveys do not provide any reliable means forcomparing preferences across attributes. For example, conventionalsurveys are generally unable to determine the degree to which a consumerprefers a black chassis over another color so as to enable comparisonbetween that degree and the degree to which the consumer prefers a 27″screen over another screen size. As a result of these drawbacks,conventional surveys are poor at producing useful quantified preferenceinformation of individual consumers.

[0010] Focus groups are another conventional vehicle used to obtainconsumer preference information. In a typical focus group, certainconsumers are randomly selected (or selected based on demographics asdescribed above) to answer questions and/or to participate in a groupdiscussion regarding a product or a type of product. Answers andcomments put forth by the consumers are noted and tabulated to createpreference information similar to that obtained using survey techniques.However, because of their interactive nature, focus groups tend toelicit information which is more pertinent than that elicited bysurveys. Despite this advantage, focus groups still suffer from thedrawbacks described above with respect to conventional surveys.

[0011] The field of trade-off analysis developed to address the aboveand other shortcomings in conventional techniques for determiningconsumer preference information. Generally, trade-off analysistechniques attempt to quantify a consumer's preference for a particularproduct's attributes and attribute levels. Such quantification isintended to allow a manufacturer to easily and accurately compare theattractiveness of various product configurations to a consumer. Forexample, trade-off analysis techniques allow a manufacturer to comparethe attractiveness of a 27″ television with Picture-in-picturecapability priced at $399 with that of a 35″ television with a digitalcomb filter priced at $599. This comparison is possible because thetechniques associate a particular numerical value with a consumer'spreference for each attribute and attribute level. Accordingly, therelative attractiveness of any attribute or attribute level with respectto any other attribute or attribute level can be determined simply bycomparing the appropriate associated numerical values.

[0012] According to one classification scheme, four types of trade-offanalysis techniques exist: conjoint; discrete choice; self-explicated;and hybrid. Conjoint analysis generally requires a consumer to rate orrank product configurations with respect to one another. Typically, theconsumer is asked to rank twenty to thirty product configurations. Eachranked configuration includes different combinations of attributes andattribute levels being evaluated. By appropriately varying theconfigurations, a regression model can be estimated for each consumer.

[0013] Conjoint analysis is an improvement over conventional systems fordetermining consumer preferences. For example, determining preferencesby observing consumer behavior is difficult because consumer behaviorcan usually be observed only with respect to a few combinations ofattributes and attribute levels (i.e., the combinations that exist inthe marketplace). Accordingly, it becomes difficult to separate anddistinguish between the preferences of different consumers and topredict effects of changes in attributes and/or attribute levels onconsumer behavior. On the other hand, conjoint analysis allows forimproved learning of consumer preferences through controlled variationand controlled co-variation of attributes and attribute levels.

[0014] According to discrete choice analysis, a consumer is presentedwith a set of product configurations and asked to select either theconfiguration that the consumer is most interested in purchasing or noconfiguration if the consumer is not interested in purchasing any of thepresented configurations. The process is then repeated for other sets ofproduct configurations. In contrast to conjoint analysis, which may beused to estimate a regression model for individual consumers, discretechoice analysis may be used to estimate a mixture method (similar to aregression model) for a group of consumers.

[0015] While conjoint analysis and discrete choice analysis determineconsumers' preferences indirectly, self-explicated analysis directlydetermines preferences by asking consumers how important each productattribute range and attribute level range is to their purchasingdecisions. According to some self-explicated analysis models, consumersare presented with all attributes and attribute levels to be evaluated,and asked to identify attribute levels that are unacceptable. Anunacceptable attribute level is one that, if included in a product,would cause the product to be completely unacceptable to the consumer,regardless of any other attributes and attribute levels included in theproduct. For example, a consumer may indicate that an automobileincluding an attribute level of “pink” associated with the attribute“color” is completely unacceptable regardless of any other attributes orattribute levels included in the automobile. Accordingly, “pink” isidentified as an unacceptable attribute level for that consumer.

[0016] Next, the consumer is asked to identify, from the acceptableattribute levels, the most-desirable and the least-desirable attributelevels associated with each presented attribute. Assuming that theconsumer's most important attribute has a rating of 100, the consumer isthen asked to rank the relative importance of each remaining attributefrom 0 to 100. Next, for each attribute, the desirability of eachattribute level is rated with respect to all other acceptable attributelevels of the attribute. A consumer preference for an attribute level isthen obtained by multiplying the relative importance of its associatedattribute by its desirability rating.

[0017] Hybrid analysis techniques utilize a combination of features fromthe above-described techniques. The most common example of a hybridanalysis technique is Adaptive Conjoint Analysis (ACA), a product ofSawtooth Software, Inc. According to ACA, a consumer is taken throughseveral rankings of attribute levels and ratings of relative attributeimportance (similar to self-explicated techniques) and then asked toidentify, for each of a series of pairs of product configurations, whichone of the pair is the most desirable and the degree to which it is moredesirable. Other examples of hybrid models include the Cake Method andthe Logit-Cake Method developed by MACRO Consulting, Inc.

[0018] Each of these trade-off analysis techniques requires consumers toprovide consistent, thoughtful responses to presented inquiries. Aconsumer may be able to provide such responses if presented with a smallnumber of inquiries, but is unlikely to do so if presented with manyinquiries. In this regard, the number of inquiries presented by each ofthe above techniques increases sharply as the number of evaluatedattributes and/or attribute levels increases. Such an increase in thenumber of inquiries also causes a corresponding increase in the amountof time required to answer the inquiries. Therefore, as more attributesand attribute levels are evaluated, various forms of consumer bias arelikely to increase, such as a waning attention span, a lack of time, alack of patience, boredom, and haste. These increased consumer biasesresult in increased consumer error and inaccurate preferenceinformation. Also increased is a consumer's tendency to abandon thetechnique and to simply cease answering further inquiries, in which casethe resulting preference information is partially or totally unusable.

[0019] Another form of consumer bias is caused by consumer attitudestoward particular attributes and/or attribute levels. As describedabove, conventional trade-off analysis techniques ask a consumer toevaluate the importance of an attribute or attribute level with respectto other attributes or attribute levels. However, if the consumer has anextreme dislike for one of the attributes or attribute levels, theconsumer may overestimate the importance of the other attributes orattribute levels.

[0020] In view of the foregoing, what is needed is a trade-off analysissystem to quantify consumer preferences which addresses the forms ofconsumer bias experienced by conventional systems and which alsoproduces an accurate and useful picture of consumer preferences withrespect to product attributes and attribute levels.

SUMMARY OF THE INVENTION

[0021] In order to address the foregoing need, the present inventionprovides a trade-off analysis system to determine preference informationof part worth values associated with a consumer and a product. Thesystem includes determination of a plurality of attributes of theproduct, each of the plurality of attributes associated with a pluralityof attribute levels, determination of a plurality of piles of attributesbased on a first indication of the consumer, each of the plurality ofpiles comprising one or more of the plurality of attributes,determination of a ranked order of a plurality of attributes of one ofthe plurality of piles, determination of a relative importance of one ormore of the plurality of attributes of the one of the plurality of pilesbased on a second indication of the consumer, determination of a scalevalue of one or more attribute levels of the one or more of theplurality of attributes of the one of the plurality of piles based on athird indication of the consumer; and determination of a part worthvalue associated with an attribute level of one of the plurality ofattributes of the one of the plurality of piles based on a determinedscale value of the attribute level and a determined relative importanceof the one of the plurality of attributes.

[0022] By virtue of the above features, the present invention, in someaspects, reduces the consumer bias experienced by conventional systemsby reducing the number of inquiries that must be answered in order todetermine accurate and useful preference information with respect to agiven number of attributes and attribute levels. By reducing the numberof inquiries, an amount of time required from a consumer to answerinquiries is also reduced, and each of these factors reduces apossibility that a consumer will lose interest or concentration andtherefore provide inaccurate answers or stop providing answers.

[0023] Moreover, the foregoing features provide useful preference datain cases where a consumer can only be asked a limited number ofquestions or can only be asked questions over a limited time period. Inthis regard, the piles can be determined so as to limit the number ofquestions or time required to produce useful preference information.Unlike the conventional techniques mentioned above, piles also allowcustomization of attributes and attribute levels during evaluation toconsumer preference information.

[0024] Further to the above aspect, the plurality of piles may bedetermined based on an indication that one or more of the plurality ofattributes are more important to the consumer than another one or moreof the plurality of attributes. According to this further aspect, arelative importance designated by a consumer of attributes in a pile maybe more accurate since the pile includes attributes of similarimportance to the consumer. That is, designated relative importances ofeach attribute in a pile may be less likely to be skewed than as inconventional systems, where skew may result from requiring a consumer torate certain attributes relative to significantly less-important ormore-important attributes.

[0025] According to another aspect, the present invention relates to asystem to provide an offer to a consumer, including reception of anindication of a part worth value associated with the consumer and withan attribute level of an attribute of a product based on informationprovided by the consumer, determination of an offer based on the partworth value, and transmission of the offer to the consumer. In relatedaspects, the indication is determined rather than received and/or theindication is an indication of preference information. Nevertheless,these aspects allow presentation of an offer to a consumer based onpreference information of the consumer. Accordingly, the offer can bedesigned so as to maximize attractiveness to the consumer and profitreceived by the manufacturer.

[0026] In an additional aspect, the present invention concerns a systemto determine preference information associated with a consumer and aproduct, comprising transmission of a request for a ranked order of theconsumer of a plurality of attributes associated with the product, andtransmission of a request for a rating of the consumer of an importanceof at least one of the plurality of attributes relative to ahighest-ranked attribute. By separately transmitting the request for theranked order and the request for the rating according to this aspect ofthe invention, each task is made easier and confusion of the consumer isreduced. As a result, both the ranked order and the rating are likely tobe more reflective of a consumer's true preferences than in conventionalsystems which ask simply for a rating or simultaneously for a rank and arating. Moreover, this aspect allows for detection of errors in a casethat a received ranked order is inconsistent with asubsequently-received ranking.

[0027] The present invention also relates to a system to determineconsumer preference information that includes presentation of a gaminginterface to the consumer, reception of input of the consumer to thegaming interface, and determination of the consumer's preferenceinformation based on the received input. This aspect of the inventionalso reduces consumer bias by maintaining a consumer's interest inresponding and in continuing to respond to requests for input.

[0028] With these and other advantages and features that will becomehereafter apparent, a more complete understanding of the nature of theinvention can be obtained by referring to the following detaileddescription and to the drawings appended hereto.

BRIEF DESCRIPTION OF THE DRAWINGS

[0029]FIG. 1 is a flow diagram of process steps to quantify consumerpreferences according to embodiments of the present invention.

[0030]FIG. 2 is a topographic view of a network architecture accordingto embodiments of the present invention.

[0031]FIG. 3 is a block diagram of an internal architecture of a centralsystem according to embodiments to the present invention.

[0032]FIG. 4 is a block diagram of an internal architecture of a clientdevice according to embodiments to the present invention.

[0033]FIG. 5 is a representative view of a tabular portion of a productdatabase according to embodiments of the present invention.

[0034]FIG. 6 is a representative view of a tabular portion of apreference information database according to embodiments of the presentinvention.

[0035]FIG. 7 is a view of an interface used to elicit information from aconsumer according to embodiments of the present invention.

[0036]FIG. 8 is a view of an interface used to elicit information from aconsumer according to embodiments of the present invention.

[0037]FIG. 9 is a view of an interface used to elicit information from aconsumer according to embodiments of the present invention.

[0038]FIG. 10 is a view of an interface used to elicit information froma consumer according to embodiments of the present invention.

[0039]FIG. 11 is a view of an interface used to elicit information froma consumer according to embodiments of the present invention.

[0040]FIG. 12 is a view of an interface used to elicit information froma consumer according to embodiments of the present invention.

[0041]FIG. 13 is a view of consumer preference information as presentedto a client according to embodiments of the present invention.

DETAILED DESCRIPTION

[0042]FIG. 1 is a flow diagram of process steps 100 according toembodiments of the invention. Process steps 100 will be describedinitially below without reference to a specific example in the interestof providing an immediate introduction to features of the presentinvention. Accordingly, process steps 100 will be described later withrespect to a specific example and specific hardware and softwareembodiments, along with details of alternative embodiments.

[0043] Process steps 100 begin at step S102, in which a plurality ofproduct attributes are determined for a particular product. Each productattribute is associated with a plurality of attribute levels. Theproduct attributes and attribute levels may be determined based oninformation obtained from a manufacturer of the product. Generally, theattributes and attribute levels are features for which the manufacturerwishes to obtain consumer preference information. It should beunderstood that, although the present disclosure primarily discussesmanufacturers, the present invention may be utilized by sellers,distributors or other parties interested in obtaining consumerpreference information. Moreover, the term products is used herein torefer to products and/or services.

[0044] After step S102, a plurality of piles of attributes aredetermined based on a first indication of a consumer in step S104. Eachof the plurality of piles includes one or more product attributes. Inorder to determine the plurality of piles, the consumer is asked togroup the plurality of product attributes according to their importance.For example, the attributes may be grouped into three piles representingleast-important attributes, most-important attributes, and otherattributes. Flow then proceeds to step S106.

[0045] In step S106, a ranked order of a plurality of attributes of oneof the plurality of piles is determined. Step S106 is performed byreceiving a ranking of each attribute in a pile from a consumer anddetermining a ranked order therefrom. Next, in step S108, a relativeimportance of one or more of the plurality of attributes of the pile toanother attribute of the pile is determined based on a second indicationof the consumer. The second indication is prompted by transmission of aquestion to the consumer such as “How important is the differencebetween (attribute level X) and (attribute level Y) of (attribute 1)relative to the difference between (attribute level A) and (attributelevel B) of (attribute 2)?” The importance value is expressed in termsof a percentage, with the most-important attribute being associated withan importance value of 100%. In one embodiment, after completion of stepS108, each of the one or more attributes of one of the plurality ofpiles is associated with a relative importance value. In anotherembodiment, only a portion of the one or more attributes of the one ofthe plurality of piles are associated with a relative importance value.

[0046] A scale value of one or more attribute levels of the pile is thendetermined in step S110 based on a third indication from the consumer.In order to determine a scale value, an indication from a consumer isreceived which assigns a value of 0 to a least-desirable attribute levelassociated with a particular attribute, and a value of 10 to amost-desirable attribute level associated with the particular attribute.Furthermore, the indication assigns each other attribute levelassociated with the particular attribute a value between 0 and 10. Ascale value of an attribute level may be generated by asking theconsumer to rate the scale value with respect to the least-desirable andthe most-desirable attribute levels

[0047] Next, a part worth value is determined in step S112. A part worthvalue is a value which represents a consumer's preference, or utility,for a particular attribute level. Advantageously, part worth valuesaccording to embodiments of the invention may be used to comparedifferences in attribute levels associated with different attributes interms of their respective desirability.

[0048] The part worth value determined in step S112 is associated withan attribute level of one of the plurality of attributes of the pile.Specifically, the part worth value is determined by multiplying a scalevalue of the attribute level (determined in step S110) by the relativeimportance of the associated attribute (determined in step S108). Forexample, the part worth value of the most-desirable attribute level ofthe most-important attribute equals 10×100%=10, while the part worthvalue of the least-desirable attribute level of the most-importantattribute equals 0×100%=0. As can be understood, the part worth value ofa least-important attribute level associated with any attribute equals0.

[0049] As described above, embodiments of process steps 100 reducepotential consumer bias by reducing a number of inquiries that must beanswered in order to determine accurate and useful preferenceinformation. The reduced number of inquiries and reduced amount of timerequired from a consumer to answer inquiries decreases a possibilitythat a consumer will lose interest or concentration and thereforeprovide inaccurate answers. Moreover, reduction in the number ofinquiries results in less data to store and to analyze.

[0050] Process steps 100 may also provide useful preference data incases where a consumer can only be asked a limited number of questionsor can only be asked questions over a limited time period. In thesecases, the piles can be determined so as to limit the number ofquestions or time required to produce useful preference information.Further, in cases where the plurality of piles are determined based onan indication that one or more of the plurality of attributes are moreimportant to the consumer than another one or more of the plurality ofattributes, a consumer may more accurately provide a relative importanceof each attribute in a pile. Thusly-provided relative importances arebelieved to be more accurate since the importances are less likely to beskewed by the consumer's feelings toward an attribute in the pile thatis significantly less important or more important than other attributesin the pile.

Network Architecture

[0051]FIG. 2 is a topographic view of a network architecture accordingto embodiments of the present invention. Of course, many otherarchitectures may be used to implement the invention. Shown in FIG. 2 iscentral system 200, depicted as a mainframe computer. Central system 200may be used to perform the process steps 100 of FIG. 1 in order todetermine preference information of part worth values associated with aconsumer and a product. Central system 200 may be operated by a company,such as assignee Blue Flame Data, Inc., providing trade-off analysisservices to manufacturers or other clients desiring to obtain consumerpreference information.

[0052] In operation, central system 200 may use data input by consumersand clients, as well as legacy data, third party data and/or observedbehavior data to produce such preference information. It should be notedthat many other types of computing hardware may be used to perform thefunctions of central system 200, including, but not limited to, aserver, a workstation, a network, or any combination of one or more ofthe foregoing. Further details of central system 200 are set forth belowwith respect to FIG. 3.

[0053] In communication with central system 200 are several clientdevices 300. Client devices 300 according to the present invention maybe used by a product manufacturer to transmit attributes and attributelevels for a given product to central system 200 in order to havecentral system 200 determine part worth values associated with eachattribute and attribute level. Of course, central system 200 maydetermine the attributes and attribute levels using data from othersources. Other information which may be transmitted from client devices300 to central system 200 includes information for modifying thresholdsor other parameters used by the central system 200 to determinepreference information according to the present invention.

[0054] Client devices 300 may also receive information from centralsystem 200 intended for display to a manufacturer or another client.Such information may include real-time monitoring of consumer responses,scenario simulations, or an interface allowing the operator to tweakexisting thresholds or parameters while information is being gatheredfrom consumers. Of course, the manufacturer may also use client device300 to view preference information received from central system 200 byclient device 300.

[0055] As shown in FIG. 2, client device 300 may include a server and/ora kiosk. Any other suitable device may be used as client device 300according to the invention, including but not limited to a workstation,a mainframe computer, and a computer terminal. In the case that clientdevice 300 is a device having its own input and/or output devices, suchas a kiosk, a consumer may also use client device 300 to input answersto inquiries posed according to the invention and to input otherindications to central system 200. Accordingly, client device 300 mayalso be used in such a case to present an interface to the consumer thatallows the consumer to input such information.

[0056] Information may also be transmitted to or received from consumersas described above through consumer devices 400. Shown in FIG. 2 areconsumer devices 400 represented by a telephone, a personal digitalassistant, a workstation, and a pen-based computer. The shown consumerdevices 400 are used to communicate with client devices 300 and, in thecase of telephone consumer device 400, directly with central system 200.In this regard, consumer devices 400 usable in conjunction with thepresent invention include any device capable of presenting informationto a consumer, visually and/or aurally, and of transmitting anindication made by the consumer to an external device. Of course,consumer devices 400 should be able to communicate with the device ordevices with which they are in communication over whatever type ofnetwork media exist between the devices.

[0057] Although the connections illustrated between the components ofFIG. 2 appear dedicated, it should be noted that each of the connectionsmay be shared by other components. Moreover, the connections maycomprise one or more of a local area network, a wide area network, atelephone network, a cellular network, a fiber-optic network, asatellite network, an infra-red network, a radio frequency network, orany other type of network which may be used to transmit informationbetween devices. Additionally, the devices shown as in communicationwith other devices need not be constantly exchanging data, rather, thecommunication may be established when necessary and severed at othertimes or always available but rarely used to transmit data.

Central System

[0058]FIG. 3 is a block diagram of the internal architecture of centralsystem 200 according to embodiments of the invention. As illustrated,central system 200 includes microprocessor 210 in communication withcommunication bus 220. Microprocessor 210 may be a Pentium, RISC-based,or other type of processor and is used to execute processor-executableprocess steps so as to control the components of central system 200 toprovide desired functionality.

[0059] Also in communication with communication bus 220 is communicationport 230. Communication port 230 is used to transmit data to and toreceive data from external devices. Communication port 230 is thereforepreferably configured with hardware suitable to physically interfacewith desired external devices and/or network connections. In oneembodiment, inquiries to present to consumers and indications fromconsumers are transmitted to and received from client devices 300 overcommunication port 230.

[0060] Input device 240, display 250 and printer 260 are also incommunication with communication bus 220. Any known input device may beused as input device 240, including a keyboard, mouse, touch pad,voice-recognition system, or any combination of these devices. Inputdevice 240 may be used by an operator to input product-relatedinformation such as attributes and attribute levels, consumer-relatedinformation such as contact and identification information,client-related information such as billing and transaction information,and commands to central system 200. In this regard, a command may beinput to central system 200 to output a report detailing a particularclient's account or a particular consumer's preference information.

[0061] Such a report may be output to display 250, which may be anintegral or separate CRT display, flat-panel display or the like.Display 250 is used to output graphics and text to an operator inresponse to commands issued by microprocessor 210. Printer 260 is alsoan output device, but produces a hardcopy of data using ink-jet,thermal, dot-matrix, laser, or other printing technologies.

[0062] RAM 270 is connected to communication bus 220 to providemicroprocessor 210 with fast data storage and retrieval. In this regard,processor-executable process steps being executed by microprocessor 210are typically stored temporarily in RAM 270 and executed therefrom bymicroprocessor 210. ROM 280, in contrast, provides storage from whichdata can be retrieved but to which data cannot be stored. Accordingly,ROM 280 is used to store invariant process steps and other data, such asbasic input/output instructions and data used during system boot-up orto control communication port 230.

[0063] Data storage device 290 stores, among other data, central systemprogram 292 of processor-executable process steps. According toembodiments of the present invention, the process steps of centralserver program 292 may be read from a computer-readable medium, such asa floppy disk, a CD-ROM, a DVD-ROM, a Zip disk, a magnetic tape, or asignal encoding the process steps, and then stored in data storagedevice 290. Microprocessor 210 executes instructions of program 292, andthereby operates in accordance with the present invention, andparticularly in accordance with the process steps described in detailherein.

[0064] Specifically, according to embodiments of the invention,microprocessor 210 executes processor-executable process steps ofcentral system program 292 to provide for determination of a pluralityof attributes of a product, each of the plurality of attributesassociated with a plurality of attribute levels, determination of aplurality of piles of attributes based on a first indication of aconsumer, each of the plurality of piles comprising one or more of theplurality of attributes, determination of a ranked order of a pluralityof attributes of one of the plurality of piles, determination of arelative importance of one or more of the plurality of attributes of theone of the plurality of piles based on a second indication of theconsumer, determination of a scale value of one or more attribute levelsof the one or more of the plurality of attributes of the one of theplurality of piles based on a third indication of the consumer; anddetermination of a part worth value associated with an attribute levelof one of the plurality of attributes of the one of the plurality ofpiles based on a determined scale value of the attribute level and adetermined relative importance of the one of the plurality ofattributes.

[0065] Also according to embodiments of the invention, the process stepsallow for reception (or determination) of an indication of a part worthvalue (or of preference information) associated with a consumer and withan attribute level of an attribute of a product based on informationprovided by the consumer, determination of an offer based on the partworth value, and transmission of the offer to the consumer. Moreover,the process steps provide a system to determine preference informationthrough a first transmission of a request for a ranked order of aconsumer of a plurality of attributes associated with a product, and asecond transmission of a request for a rating of the consumer of animportance of at least one of the plurality of attributes relative to ahighest-ranked attribute.

[0066] In alternative embodiments, hard-wired circuitry may be used inplace of, or in combination with, processor-executable process steps forimplementation of the processes of the present invention. Thus,embodiments of the present invention are not limited to any specificcombination of hardware and software.

[0067] Also included in central system program 292 may beprocessor-executable process steps to provide a World Wide Web server.Such a Web server would allow central server 200 to communicate withclient devices 300 and consumer devices 400 through the World Wide Web.In addition, program 292 may include process steps of an interactivevoice response system enabling central system 200 to transmit inquiriesto and receive responses from a consumer using a telephone consumerdevice 400.

[0068] Central system program 292 may be stored in data storage device290 in a compressed, uncompiled and/or encrypted format. Central systemprogram 292 furthermore includes program elements that may be necessaryfor operation of central system 292, such as an operating system, adatabase management system and “device drivers” for allowingmicroprocessor 210 to interface with devices in communication withcommunication port 230. These program elements are known to thoseskilled in the art, and need not be described in detail herein.

[0069] Also stored in data storage device 290 is product database 294and preference information database 296. Product database 294 includesinformation regarding products for which preference information has beenor will be determined and preference information database 296 includespreference information determined according to the present invention.These databases will be discussed in detail with reference to FIGS. 5and 6, respectively.

Client Device

[0070]FIG. 4 illustrates an internal architecture of client device 300.As shown, client device 300 according to the depicted embodimentincludes microprocessor 310, communication port 330, input device 340,display 350, printer 360, RAM 370 and ROM 380, each of which is incommunication with communication bus 320. Possible embodiments for eachof these components are similar to those described with respect toidentically-named components of FIG. 3, although functions performed bythe components of FIG. 4 according to the invention may differ fromthose performed by the components of FIG. 3.

[0071] Specifically, input device 340 may be used by a manufactureroperating client device 300 to input product attributes and attributelevels for which preference information is sought, and also to inputdemographic information of a typical consumer from whom preferenceinformation is desired. Display 350 and printer 360 may be used tooutput information received from central system 200, such as consumerpreference information, a recommended offer, an optimal product, or aconsumer's willingness to pay. Of course, this information may bedetermined by client device 300 instead of being received from centralsystem 200. In a case that client device 300 is a kiosk or other deviceusable by both a consumer and a client manufacturer, input device 340,display 350 and printer 360 may also be used by a consumer to receiveinquiries from and to input answers to inquiries and other indicationsto central system 200.

[0072] Data storage device 390 stores client device program 392, productdatabase 394 and preference information database 396. Client deviceprogram 392 includes processor-executable process steps which may beexecuted by microprocessor 310 to perform the process steps describedherein. According to embodiments of the invention, client device program392 includes process steps providing reception of an indication of apart worth value associated with the consumer and with an attributelevel of an attribute of a product based on information provided by theconsumer, determination of an offer based on the part worth value, andtransmission of the offer to the consumer. As described above, suchfunctionality allows presentation of an offer to a consumer that istailored to the specific preference information of the consumer.

[0073] Client device program 392 may also include processor-executableprocess steps to provide a World Wide Web server. As described withrespect to central system 200, a Web server would allow client device300 to communicate with consumer devices 400 executing a Web browser.Client device program 392 may additionally include process steps of aninteractive voice response system that provides automated communicationwith a consumer using a telephone consumer device 400.

[0074] The process steps of client device program 392 may be receivedfrom any computer-readable medium for storage in data storage device390. According to some embodiments, client device program 392 isreceived from the entity operating central system 200 as part of abusiness solution offered by the entity. In this regard, the stepsdescribed above with respect to FIG. 1 and otherwise in conjunction withthe invention may be performed by one or cooperatively by both ofcentral system 200 and client device 300.

[0075] Product database 394 includes information similar to thatincluded in product database 294. The information included in productdatabase 394, however, is input in some embodiments by a manufactureroperating client device 300. Preference information database 396includes consumer preference information that may be transmitted bycentral system 200 to client device 300 or may be generated by clientdevice 300 according to the invention.

[0076] As mentioned above, product database 294 and preferenceinformation database 296 are described in detail below and depicted withsample entries in FIGS. 5 and 6. As will be understood by those skilledin the art, the tabular illustrations and accompanying descriptions ofthe databases merely represent relationships between stored information.A number of other arrangements may be employed besides those suggestedby the tables shown. Similarly, the illustrated entries of the databasesrepresent sample information only; those skilled in the art willunderstand that the number and content of the entries can be differentfrom those illustrated.

Product Database

[0077] A tabular representation of a portion of product database 294 isshown in FIG. 5. Product database 294 stores data specifying attributesand associated attribute levels for particular products. Specifically,client:product field 402 indicates a client for whom the associatedattributes 404 and attribute levels 406 are to be evaluated and aproduct with which the attributes 404 and attribute levels 406 areassociated. Also associated with attribute 404 and attribute levels 406in a single record is an implicit order flag 408. Implicit order flag408 indicates whether or not associated attribute levels 406 can beassumed to be listed in order of consumer preference. Usage of implicitorder flag 408 will be described below. It should be noted thatattributes 404, attribute levels 406, and implicit order flags 408 maybe specified by a consumer or by a client and received by central system200 from client device 300 or from consumer device 400. Of course,attributes 404, attribute levels 406, and implicit order flags 408 ofproduct database 294 may also be determined by central system 200independently.

[0078] Although shown in FIG. 5 are data specifying particularattributes and attribute levels, the invention contemplates evaluatingfewer or more attributes and/or attribute levels for any particularproduct. Additionally, it is contemplated that product database 294 maystore data for multiple products and/or multiple clients. In contrast,it is contemplated for one embodiment that product database 394 storedin client device 300 might store only data associated with theparticular client operating client device 300.

[0079] The data stored in product database 294 may be used in accordancewith embodiments of the present invention to determine preferenceinformation relating to the attributes 404 and attribute levels 406. Onesuch embodiment was described above with respect to FIG. 1. After suchdetermination, the preference information may be stored in preferenceinformation database 296, and/or transmitted to client device 300 forstorage in preference information database 396.

Preference Information Database

[0080]FIG. 6 shows a tabular representation of a portion of preferenceinformation database 296 according to embodiments of the invention. Thedata stored in preference information database 296 reflects preferenceinformation determined according to the invention. As shown byconsumer:product field 410, the portion of the database shown reflectspreference information of a single consumer with respect to a singleproduct. Each record in the tabular portion includes a field specifyingan attribute 412 and a field 414 specifying corresponding attributelevels as well as part worth values associated with each attributelevel.

[0081] As mentioned with respect to product database 294, the datastored in preference information database 296 for a particular productmay reflect fewer or more attributes and/or attribute levels than shownin FIG. 6. Furthermore, it is contemplated that preference informationdatabase 296 will store data corresponding to multiple consumers and tomultiple products for each consumer. On the other hand, it iscontemplated that product database 396 of client device 300 might storepreference information of multiple consumers but corresponding only tothose products to be sold by the particular client operating clientdevice 300. As will be understood, those part worth values indicated as“?” are associated with attributes 412 deemed “less important” by aconsumer.

Specific Example

[0082] Although the example below is based on the FIG. 1 process steps,contemplated additional and/or alternative processing will also bedescribed. It should be noted that the process steps of FIG. 1 and theother process steps described herein are described as being performed bycentral system 200 through execution of processor-executable processsteps of central server program 292 by microprocessor 210. However, theprocess steps may also be performed, in whole or in part, by one or moreof central system 200, client devices 300, consumer devices 400, anotherdevice, and manual means.

[0083] As described above, a plurality of product attributes for asubject product is determined in step S102. In the example set forthbelow, the subject product is a luxury passenger automobile, and theattributes are “Horsepower”, “Miles per gallon (M.P.G.)”, “Make” and“Price”. Each determined attribute is associated with one or moreattribute levels, which are shown associated with the attributes inproduct database 294 of FIG. 5. Accordingly, the attributes may bedetermined by central system 200 in step S102 by referring to attributesassociated with the stored product in product database 294. Theattributes may also be determined by central system 200 by receivingdata representing the attributes from an operator via input device 240or by receiving data representing the attributes from client device 300.In the latter case, client device 300 may retrieve the attributes fromproduct database 394 or from an operator operating input device 340.Moreover, the attributes may be determined in step S102 by receiving theattributes from a consumer after identifying the product to theconsumer. In this regard, the consumer may be asked to select or specifythe attributes and/or attribute levels which are of concern to him whendeciding whether to purchase the product.

[0084] After the attributes are determined, it is determined whether anyattribute levels associated with the determined attributes areunacceptable to the consumer. In this regard, an unacceptable attributelevel is an attribute level that, if included in a product, wouldprevent the consumer from purchasing the product, regardless of otherattribute levels that may be included in the product. User interface 500of FIG. 7 may be used to determine unacceptable attributes based oninput from a consumer.

[0085] User interface 500 is presented to a consumer via consumer device400. User interface 500, as well as the other user interfaces describedbelow, may originate at central system 200 and be transmitted toconsumer device 400 directly from central system 200 or from centralsystem 200 through an intermediate device such as client device 300.Similarly, the user interfaces may originate at client device 300 and betransmitted to consumer device 400 directly or through an intermediatedevice.

[0086] User interface 500, as shown, asks the consumer to identifyunacceptable attribute levels of the determined attributes. Theinformation included in user interface 500 reflects the informationstored in product database 294 of central system 200. Using userinterface 500, the consumer may identify from zero to all of thedisplayed attribute levels as being unacceptable. As shown in FIG. 7,the consumer has identified “150 hp”, “15 M.P.G”, and “$50,000” asunacceptable attribute levels.

[0087]FIG. 8 shows user interface 600, which may be presented to aconsumer following user interface 500. User interface 600 presentsattributes along with associated attribute levels that are not indicatedas unacceptable in user interface 500. Accordingly, FIG. 8 shows all theattributes and attribute levels shown in FIG. 7 except for thoseattribute levels deemed unacceptable. User interface 600 asks theconsumer to identify the most-desirable and the least-desirable of theshown attribute levels. Alternatively, user interface 600 may ask theconsumer to rank the desirability of each of the shown attribute levelsof an attribute.

[0088] According to embodiments of the invention, an attribute and itsassociated attribute levels might not be shown in user interface 600 ifthe attribute levels have an implicit order. An implicit order is aranked order of the desirability of attribute levels which is assumedbased on expected consumer desires. For example, product database 294indicates that the attribute levels of the attribute “Price” are listedin implicit order, as it may be assumed that a consumer would prefer,for example, a $30,000 automobile over a $35,000 automobile, all elsebeing equal.

[0089] Alternatively, attribute levels having an implicit order may beshown in user interface 600, with the associated check boxes pre-checkedbased on the implicit order. Using the present example, such anembodiment would pre-check the check boxes indicating that “$30,000” isa most-desirable attribute level and that “$45,000” is a least-desirableattribute level of the attribute “Price”.

[0090] After the most-desirable and least-desirable attribute levels aredetermined, user interface 700 is presented in order to determine aplurality of piles of attributes based on an indication of the consumer,as described above with respect to step S104. As shown in FIG. 9, userinterface 700 asks the consumer to identify each attribute as either“important” or “less important”. The consumer manipulating userinterface 700 of FIG. 9 has indicated that the attributes “Horsepower”,“M.P.G” and “Price” are “important” and that the attribute “Make” is“less important”. In terms of the present disclosure, the “important”and “less important” designations refer to separate attribute piles. Itshould be noted that more than two piles may be determined in accordancewith the present invention, such as “very critical”, “moderatelycritical”, and “non-critical” piles. In other embodiments, userinterface 700 is presented to a consumer to group attributes into pilesonly if the number of attributes is greater than a threshold. Thethreshold may depend on the amount of time in which the process must becompleted or on a maximum number of questions to be asked to theconsumer, and may be set by central system 200, client device 300 orconsumer device 400.

[0091] Next, according to step S106, user interface 800 of FIG. 10 ispresented to the consumer so as to determine a ranked order of theattributes included in the “important” pile. Although user interface 800allows ranking by assigning numbers to each attribute, a ranked ordermay also be determined by asking the consumer to specify a difference indesirability of the most-desirable and the least-desirable attributelevel for each attribute. The attributes are then ranked according tothe differences, with the attribute having the greatest difference beingthe most-important attribute.

[0092] User interface 900 of FIG. 11 is then presented to the consumerto determine a relative importance of the attributes of the “critical”pile with respect to the most-important attribute. By determiningrelative importances after determining a ranked order, the processallows a consumer to make general relative comparisons betweenattributes before making more detailed relative comparisons. As aresult, a consumer is able to more accurately assign relativeimportances to attributes than with prior systems.

[0093] In the embodiment of FIG. 11, the importance is determined byasking the consumer to rate, for each attribute other than themost-important attribute, the importance of the most-desirable attributelevel versus the least-desirable attribute level as compared to theimportance of the most-important attribute's most-desirable attributelevel versus its least-desirable level. In the specific example, themost-important attribute was indicated as “Horsepower” using userinterface 800, and the most-desirable and least-desirable attributelevels of the attributes “Price” and “Horsepower” were noted as“$30,000”, “$45,000”, “250 Hp”, and “190 Hp”, respectively, in the userinterface 600. Therefore, user interface 900 asks the consumer to ratethe importance of a $30,000 price to a $45,000 price as compared to theimportance of the difference in horsepower. Also according to theexample, the same question is asked with respect to the most-desired andleast-desired attribute levels of “M.P.G.”, the remaining attribute ofthe “important” pile.

[0094] In one embodiment, the above question is asked with respect toeach attribute according to ranked order. That is, a relative importanceof a second-ranked attribute is determined before the relativeimportance of a third-ranked attribute. Such an embodiment allows aconsumer to more precisely indicate relative importances thanembodiments in which the importances are not determined according toranked order.

[0095] According to other embodiments, the consumer is asked to rate theimportance of fewer than all of the remaining attributes of the“important” pile. For example, a consumer may be asked to rank theimportance of the top 20 attributes or the top 20% of attributes in the“important” pile, based on the determined ranked order. The amount ofattributes rated may be selected by the client, selected by theconsumer, or assumed by central system 200 based on any factor,including a time allotted to receive information from the consumer. Theunrated attributes according to these embodiments may be assignedimportances based on their relative ranks. In this regard, in a casethat a sixth-lowest ranked attribute is assigned a relative importanceof 12%, the attributes having the five lowest ranks may be automaticallyassigned relative importances of 10%, 8%, 6%, 4%, and 2%, respectively.These embodiments advantageously provide accurate preference informationwhile reducing an amount of time required to receive information from aconsumer and thereby reducing several consumer biases.

[0096] The relative importances of all attributes may also be determinedby designating the most-important attribute as having a relativeimportance of 100% and asking the consumer to specify percentage valuesfor each other attribute in the pile. Moreover, the relative importanceof an attribute may be determined by evaluating a rating of the consumerof the importance of the difference between the most-desirable andleast-desirable attribute levels of the attribute relative to thedifference between the most-desirable and least-desirable attributelevels of the most-important attribute.

[0097] Additionally, the relative importance may be determined in stepS108 through a consumer rating of the importance of the differencebetween the most-desirable and least-desirable attribute levels of theattribute relative to the difference between the most-desirable andleast-desirable attribute levels of the least-important attribute. Therelative importances may also be based on the attribute ranking receivedthrough user interface 800, wherein, for example, the most-importantattribute is assigned a 100% relative importance, the least-importantattribute is assigned a 0% importance and the remaining attributes arespaced evenly within the intervening range.

[0098] Next, in step S110, scale values of each acceptable attributelevel of the attributes in the “important” pile are determined. Userinterface 1000 illustrates one method of eliciting from the consumer thescale value of each attribute level associated with an attribute. In thepresent example, scale values need not be determined for thoseattributes of the pile associated with only two attribute values, suchas “M.P.G.”, since the remaining attribute levels are, by definition,the most-desirable and the least-desirable attribute levels andautomatically assigned scale values of 10 and 0, respectively. As shown,the scale values may be determined as “5” for “220 hp” and “3” and “7”for each of “$40,000” and “$35,000”.

[0099] The scale values may be determined based on a response to aquestion such as “How would you feel if you received a car having 220 Hpinstead of 250 Hp, all else being equal?”, in which the response may beone of a range of responses. Other methods include allowing the consumerto assign scale values to each attribute level. These methods allowchecking of the accuracy of the consumer's responses, because theassigned scale values can be checked for inconsistency with theattribute level ranking input to user interface 600. For example, aninconsistency may be identified if “190 Hp” is indicated as aleast-desirable attribute level but is given a scale value greater thanthe scale value of “220 Hp”. The scale values may also be determinedbased solely on attribute level rankings, with a most-importantattribute level and a least-important attribute level assigned to values10 and 0, respectively, and with remaining attribute levels assignedvalues resulting in equidistant spacing of all the attribute levels.

[0100] After determination of the scale values, a part worth value ofeach attribute level may be determined based on the associated scalevalue and the relative importance of the associated attributes. In thepresent example, attribute level “220 hp” was determined to have a scalevalue of “5” based on consumer input to user interface 1000.Additionally, “Horsepower” was determined to be the most-importantattribute based on input to user interface 800, and therefore wasassigned a relative importance of 100% in step S108. Accordingly, thepart worth value associated with “220 hp” is (100%×5)=5. Similarly, thepart worth values corresponding to “190 hp” and “250 hp” are (100%×0)=0and (100%×10)=10, respectively.

[0101] Taking the assumption that the relative importances determined instep S108 for attributes “M.P.G.” and “Price” are 40% and 70%,respectively, preference information database 294 of FIG. 6 is populatedwith preference information determined according to the present exampleof an embodiment of the invention. More specifically, the part worthvalues associated with “M.P.G” attribute levels “25 M.P.G.” and “35M.P.G.” are (40%×0)=0 and (40%×10)=4, and the values associated with“Price” attribute levels “$45,000”, “$40,000”, “$35,000”, and “$30,000”are (70%×0)=0, (70%×3)=2.1, (70%×7)=4.9, and (70%×10)=7, respectively.

[0102] “?” symbols are shown in association with “Make” attribute levelsbecause the attribute “Make” was placed in a “non-critical” pile and notevaluated in the example. Additionally, an unacceptable attribute levelhas no part worth value and the associated value is thereforerepresented by “X”. In other embodiments, the part worth values ofattribute levels associated with “non-critical” attributes are estimatedbased on the previously-determined ranks of the attribute levels.

[0103]FIG. 13 is a view of consumer preference information 1100 aspresented to a client according to embodiments of the present invention.Consumer preference information 1100 is intended to provide a clientwith a comprehensible breakdown of consumer preference informationdetermined according to the present invention. Preference information1100 may be presented to the client in many ways, including bytransmitting data representing preference information 1100 to clientdevice 300, by transmitting a Web page including preference information1100 to client device 300, by displaying preference information 1100 tothe client using display 250 or display 350, and by providing to theclient a hardcopy of preference information 1100 produced using printer260 or printer 360. As shown, preference information 1100 reflects thedata stored in preference information database 296 of FIG. 6.

[0104] Although the present invention has been described with respect toparticular embodiments thereof, those skilled in the art will note thatvarious substitutions may be made to those embodiments described hereinwithout departing from the spirit and scope of the present invention.

What is claimed is:
 1. A method for determining preference informationof part worth values associated with a consumer and a product,comprising: determining a plurality of attributes of the product, eachof the plurality of attributes associated with a plurality of attributelevels; determining a plurality of piles of attributes based on a firstindication of the consumer, each of the plurality of piles comprisingone or more of the plurality of attributes; determining a ranked orderof a plurality of attributes of one of the plurality of piles;determining a relative importance of one or more of the plurality ofattributes of the one of the plurality of piles based on a secondindication of the consumer; determining a scale value of one or moreattribute levels of the one or more of the plurality of attributes ofthe one of the plurality of piles based on a third indication of theconsumer; and determining a part worth value associated with anattribute level of one of the plurality of attributes of the one of theplurality of piles based on a determined scale value of the attributelevel and a determined relative importance of the one of the pluralityof attributes.
 2. A method according to claim 1, wherein the pluralityof piles are determined based on an indication that one or more of theplurality of attributes are more important to the consumer than anotherone or more of the plurality of attributes.
 3. A method according toclaim 1, further comprising: determining a ranked order of a pluralityof attribute levels associated with one of the plurality of attributes.4. A method according to claim 3, wherein the step of determining theranked order of the plurality of attribute levels associated with one ofthe plurality of attributes comprises: receiving an indication of theattribute level of the plurality of attribute levels associated with theone of the plurality of attributes that is most desirable to theconsumer and an indication of the attribute level of the plurality ofattribute levels associated with one of the plurality of attributes thatis least desirable to the consumer.
 5. A method according to claim 3,wherein the step of determining the ranked order of the plurality ofattribute levels associated with one of the plurality of attributescomprises: determining the ranked order of the plurality of attributelevels based on expected consumer preferences.
 6. A method according toclaim 1, wherein the ranked order of the plurality of attributes isdetermined based on a difference between an attribute level most desiredby the consumer and an attribute level least desired by the consumer. 7.A method according to claim 6, wherein an attribute of the plurality ofattributes of the one of the plurality of piles having a greatestdifference between an attribute level most desired by the consumer andan attribute level least desired by the consumer is a highest rankedattribute of the one of the plurality of piles.
 8. A method according toclaim 7, wherein the step of determining a relative importance of one ormore of the plurality of attributes of the one of the plurality of pilescomprises: determining an importance to the consumer of a differencebetween an attribute level of the highest ranked attribute that is mostdesired by the consumer and an attribute level of the highest rankedattribute that is least desired by the consumer with respect to thedifference between an attribute level that is most desired by theconsumer and an attribute level that is least desired by the consumer ofone or more of the other of the plurality of attributes of the one ofthe plurality of piles.
 9. A method according to claim 1, wherein thestep of determining a relative importance of one or more of theplurality of attributes comprises: determining a relative importance ofonly each of a threshold number of the plurality of attributes.
 10. Amethod according to claim 9, wherein a relative importance of each ofthe plurality of attributes other than the threshold number of theplurality of attributes is determined based on the ranked order.
 11. Amethod according to claim 1, wherein the step of determining the partworth value associated with the attribute level of the one of theplurality of attributes comprises: determining the part worth valuebased on the relative importance of the one of the plurality ofattributes multiplied by the scale value of the attribute level.
 12. Amethod according to claim 1, further comprising eliminating an attributelevel that is unacceptable to the consumer prior to determining a rankedorder of one or more of the plurality of attributes.
 13. A methodaccording to claim 1, further comprising providing an offer to theconsumer based on the part worth value.
 14. A method according to claim1, wherein the offer is an offer to sell the product to the consumer.15. A method according to claim 1, further comprising determiningwhether a number of the plurality of attributes is greater than athreshold.
 16. A method according to claim 15, wherein the threshold isbased on an amount of time in which questions may be asked to theconsumer.
 17. A method according to claim 15, wherein the threshold isbased on a number of questions that may be asked to the consumer.
 18. Amethod for providing an offer to a consumer, comprising: receiving anindication of a part worth value associated with the consumer and withan attribute level of an attribute of a product based on informationprovided by the consumer; determining an offer based on the part worthvalue; and transmitting the offer to the consumer.
 19. A methodaccording to claim 18, further comprising: receiving an indication ofthe consumer's interest in the product.
 20. A method according to claim18, wherein the offer is an offer to sell the product to the consumer.21. A method for providing an offer to a consumer, comprising:determining a part worth value associated with the consumer and with anattribute level of an attribute of a product based on informationprovided by the consumer; determining an offer based on the part worthvalue; and transmitting the offer to the consumer.
 22. A methodaccording to claim 21, further comprising: receiving an indication ofthe consumer's interest in the product.
 23. A method according to claim21, wherein the offer is an offer to sell the product to the consumer.24. A method for providing an offer to a consumer, comprising:determining preference information associated with the consumer and withan attribute level of an attribute of a product based on informationprovided by the consumer; determining an offer based on the preferenceinformation; and transmitting the offer to the consumer.
 25. A methodaccording to claim 24, further comprising: receiving an indication ofthe consumer's interest in the product.
 26. A method according to claim24, wherein the offer is an offer to sell the product to the consumer.27. A method for determining preference information associated with aconsumer and a product, comprising: transmitting a first request for aranked order of the consumer of a plurality of attributes associatedwith the product; and transmitting a second request for a rating of theconsumer of an importance of at least one of the plurality of attributesrelative to a highest-ranked attribute of the ranked order.
 28. A methodaccording to claim 27, wherein the ranked order is based on adifference, for one or more of the plurality of attributes, between amost-desirable attribute level and a least-desirable attribute level.29. A method according to claim 28, wherein the highest-ranked attributeis an attribute of the plurality of attributes having a greatestdifference between a most-desirable attribute level and aleast-desirable attribute level.
 30. A method according to claim 27,wherein the ranked order comprises a unique rank associated with each ofthe plurality of attributes.
 31. A method according to claim 27, whereinthe rating is based on an importance to the consumer of a differencebetween an attribute level of the highest-ranked attribute that is mostdesired by the consumer and an attribute level of the highest-rankedattribute that is least desired by the consumer with respect to thedifference between an attribute level that is most desired by theconsumer and an attribute level that is least desired by the consumer ofthe at least one of the plurality of attributes.
 32. A method accordingto claim 27, further comprising determining whether the ranked order isinconsistent with the rating of the at least one of the plurality ofattributes.